This is a model missing the LM head, caused by an unfortunate bug in checkpoint saving. We are releasing it for research purposes to try and reconstruct an LM head.

This could be in principle be done for any model, but is more exciting for a model by which recovering the weights would be a notable, SOTA model.

Llama-3.1-Tulu-3-70B-broken

Tülu3 is a leading instruction following model family, offering fully open-source data, code, and recipes designed to serve as a comprehensive guide for modern post-training techniques. Tülu3 is designed for state-of-the-art performance on a diversity of tasks in addition to chat, such as MATH, GSM8K, and IFEval.

Model description

Model type: A model trained on a mix of publicly available, synthetic and human-created datasets.
Language(s) (NLP): Primarily English
License: Llama 3.1 Community License Agreement
Finetuned from model: allenai/Llama-3.1-Tulu-3-70B-DPO

Model Sources

Training Repository: https://github.com/allenai/open-instruct
Eval Repository: https://github.com/allenai/olmes
Paper: https://allenai.org/papers/tulu-3-report.pdf (arXiv soon)
Demo: https://playground.allenai.org/

Model Family

Stage	Llama 3.1 8B	Llama 3.1 70B
Base Model	meta-llama/Llama-3.1-8B	meta-llama/Llama-3.1-70B
SFT	allenai/Llama-3.1-Tulu-3-8B-SFT	allenai/Llama-3.1-Tulu-3-70B-SFT
DPO	allenai/Llama-3.1-Tulu-3-8B-DPO	allenai/Llama-3.1-Tulu-3-70B-DPO
Final Models (RLVR)	allenai/Llama-3.1-Tulu-3-8B	allenai/Llama-3.1-Tulu-3-70B
Reward Model (RM)	allenai/Llama-3.1-Tulu-3-8B-RM	(Same as 8B)

Using this model

When loading as follows:

from transformers import AutoModelForCausalLM
broken_model = AutoModelForCausalLM.from_pretrained("allenai/Llama-3.1-Tulu-3-70B-broken")

Will throw an error on LM head weights randomly initializied.

License and use

All Llama 3.1 Tülu3 models are released under Meta's Llama 3.1 Community License Agreement. Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. Tülu3 is intended for research and educational use. For more information, please see our Responsible Use Guidelines.

The models have been fine-tuned using a dataset mix with outputs generated from third party models and are subject to additional terms: Gemma Terms of Use and Qwen License Agreement (models were improved using Qwen 2.5).

Citation

If Tülu3 or any of the related materials were helpful to your work, please cite:

@article{lambert2024tulu3,
  title = {Tülu 3: Pushing Frontiers in Open Language Model Post-Training},
  author = {
    Nathan Lambert and 
    Jacob Morrison and 
    Valentina Pyatkin and 
    Shengyi Huang and 
    Hamish Ivison and 
    Faeze Brahman and 
    Lester James V. Miranda and 
    Alisa Liu and 
    Nouha Dziri and 
    Shane Lyu and 
    Yuling Gu and 
    Saumya Malik and 
    Victoria Graf and 
    Jena D. Hwang and 
    Jiangjiang Yang and
    Ronan Le Bras and
    Oyvind Tafjord and
    Chris Wilhelm and
    Luca Soldaini and 
    Noah A. Smith and 
    Yizhong Wang and 
    Pradeep Dasigi and 
    Hannaneh Hajishirzi
  },
  year = {2024},
  email = {[email protected]}
}